Genomic Signatures of Strain Selection and Enhancement in Bacillus atrophaeus var. globigii, a Historical Biowarfare Simulant

(BG) as a simulant for biological warfare (BW) agents, knowledge of its genome composition is limited. Furthermore, the ability to differentiate signatures of deliberate adaptation and selection from natural variation is lacking for most bacterial agents. We characterized a lineage of BGwith a long history of use as a simulant for BW operations, focusing on classical bacteriological markers, metabolic profiling and whole-genome shotgun sequencing (WGS). on the nucleotide level. WGS of variants revealed that several strains were mixed but highly related populations and uncovered a progressive accumulation of mutations among the “military” isolates. Metabolic profiling and microscopic examination of bacterial cultures revealed enhanced growth of “military” isolates on lactate-containing media, and showed that the “military” strains exhibited a hypersporulating phenotype.Our analysis revealed the genomic and phenotypic signatures of strain adaptation and deliberate selection for traits that were desirable in a simulant organism. Together, these results demonstrate the power of whole-genome and modern systems-level approaches to characterize microbial lineages to develop and validate forensic markers for strain discrimination and reveal signatures of deliberate adaptation

Comparative Genomics of 2009 Seasonal Plague (Yersinia pestis) in New Mexico

Plague disease caused by the Gram-negative bacterium Yersinia pestis routinely affects animals and occasionally humans, in the western United States. The strains native to the North American continent are thought to be derived from a single introduction in the late 19th century. The degree to which these isolates have diverged genetically since their introduction is not clear, and new genomic markers to assay the diversity of North American plague are highly desired. To assay genetic diversity of plague isolates within confined geographic areas, draft genome sequences were generated by 454 pyrosequencing from nine environmental and clinical plague isolates. In silico assemblies of Variable Number Tandem Repeat (VNTR) loci were compared to laboratory-generated profiles for seven markers. High-confidence SNPs and small Insertion/Deletions (Indels) were compared to previously sequenced Y. pestis isolates. The resulting panel of mutations allowed clustering of the strains and tracing of the most likely evolutionary trajectory of the plague strains. The sequences also allowed the identification of new putative SNPs that differentiate the 2009 isolates from previously sequenced plague strains and from each other. In addition, new insertion points for the abundant insertion sequences (IS) of Y. pestis are present that allow additional discrimination of strains; several of these new insertions potentially inactivate genes implicated in virulence. These sequences enable whole-genome phylogenetic analysis and allow the unbiased comparison of closely related isolates of a genetically monomorphic pathogen

Identification of Leishmania Proteins Preferentially Released in Infected Cells Using Change Mediated Antigen Technology (CMAT)

Although Leishmania parasites have been shown to modulate their host cell's responses to multiple stimuli, there is limited evidence that parasite molecules are released into infected cells. In this study, we present an implementation of the change mediated antigen technology (CMAT) to identify parasite molecules that are preferentially expressed in infected cells. Sera from mice immunized with cell lysates prepared from L. donovani or L. pifanoi-infected macrophages were adsorbed with lysates of axenically grown amastigotes of L. donovani or L. pifanoi, respectively, as well as uninfected macrophages. The sera were then used to screen inducible parasite expression libraries constructed with genomic DNA. Eleven clones from the L. pifanoi and the L. donovani screen were selected to evaluate the characteristics of the molecules identified by this approach. The CMAT screen identified genes whose homologs encode molecules with unknown function as well as genes that had previously been shown to be preferentially expressed in the amastigote form of the parasite. In addition a variant of Tryparedoxin peroxidase that is preferentially expressed within infected cells was identified. Antisera that were then raised to recombinant products of the clones were used to validate that the endogenous molecules are preferentially expressed in infected cells. Evaluation of the distribution of the endogenous molecules in infected cells showed that some of these molecules are secreted into parasitophorous vacuoles (PVs) and that they then traffic out of PVs in vesicles with distinct morphologies. This study is a proof of concept study that the CMAT approach can be applied to identify putative Leishmania parasite effectors molecules that are preferentially expressed in infected cells. In addition we provide evidence that Leishmania molecules traffic out of the PV into the host cell cytosol and nucleus

Expansion of the Human Phenotype Ontology (HPO) knowledge base and resources.

The Human Phenotype Ontology (HPO)-a standardized vocabulary of phenotypic abnormalities associated with 7000+ diseases-is used by thousands of researchers, clinicians, informaticians and electronic health record systems around the world. Its detailed descriptions of clinical abnormalities and computable disease definitions have made HPO the de facto standard for deep phenotyping in the field of rare disease. The HPO\u27s interoperability with other ontologies has enabled it to be used to improve diagnostic accuracy by incorporating model organism data. It also plays a key role in the popular Exomiser tool, which identifies potential disease-causing variants from whole-exome or whole-genome sequencing data. Since the HPO was first introduced in 2008, its users have become both more numerous and more diverse. To meet these emerging needs, the project has added new content, language translations, mappings and computational tooling, as well as integrations with external community data. The HPO continues to collaborate with clinical adopters to improve specific areas of the ontology and extend standardized disease descriptions. The newly redesigned HPO website (www.human-phenotype-ontology.org) simplifies browsing terms and exploring clinical features, diseases, and human genes

Pathosphere.org: pathogen detection and characterization through a web-based, open source informatics platform

Background The detection of pathogens in complex sample backgrounds has been revolutionized by wide access to next-generation sequencing (NGS) platforms. However, analytical methods to support NGS platforms are not as uniformly available. Pathosphere (found at Pathosphere.org) is a cloud - based open - sourced community tool that allows for communication, collaboration and sharing of NGS analytical tools and data amongst scientists working in academia, industry and government. The architecture allows for users to upload data and run available bioinformatics pipelines without the need for onsite processing hardware or technical support. Results The pathogen detection capabilities hosted on Pathosphere were tested by analyzing pathogen-containing samples sequenced by NGS with both spiked human samples as well as human and zoonotic host backgrounds. Pathosphere analytical pipelines developed by Edgewood Chemical Biological Center (ECBC) identified spiked pathogens within a common sample analyzed by 454, Ion Torrent, and Illumina sequencing platforms. ECBC pipelines also correctly identified pathogens in human samples containing arenavirus in addition to animal samples containing flavivirus and coronavirus. These analytical methods were limited in the detection of sequences with limited homology to previous annotations within NCBI databases, such as parvovirus. Utilizing the pipeline-hosting adaptability of Pathosphere, the analytical suite was supplemented by analytical pipelines designed by the United States Army Medical Research Insititute of Infectious Diseases and Walter Reed Army Institute of Research (USAMRIID-WRAIR). These pipelines were implemented and detected parvovirus sequence in the sample that the ECBC iterative analysis previously failed to identify. Conclusions By accurately detecting pathogens in a variety of samples, this work demonstrates the utility of Pathosphere and provides a platform for utilizing, modifying and creating pipelines for a variety of NGS technologies developed to detect pathogens in complex sample backgrounds. These results serve as an exhibition for the existing pipelines and web-based interface of Pathosphere as well as the plug-in adaptability that allows for integration of newer NGS analytical software as it becomes available

Bose-Einstein correlations of charged hadrons in proton-proton collisions at s\sqrt s = 13 TeV

Bose-Einstein correlations of charged hadrons are measured over a broad multiplicity range, from a few particles up to about 250 reconstructed charged hadrons in proton-proton collisions at $\sqrt{s}$ = 13 TeV. The results are based on data collected using the CMS detector at the LHC during runs with a special low-pileup configuration. Three analysis techniques with different degrees of dependence on simulations are used to remove the non-Bose-Einstein background from the correlation functions. All three methods give consistent results. The measured lengths of homogeneity are studied as functions of particle multiplicity as well as average pair transverse momentum and mass. The results are compared with data from both CMS and ATLAS at $\sqrt{s}$ = 7 TeV, as well as with theoretical predictions.[graphic not available: see fulltext]Bose-Einstein correlations of charged hadrons are measured over a broad multiplicity range, from a few particles up to about 250 reconstructed charged hadrons in proton-proton collisions at $\sqrt{s} =$ 13 TeV. The results are based on data collected using the CMS detector at the LHC during runs with a special low-pileup configuration. Three analysis techniques with different degrees of dependence on simulations are used to remove the non-Bose-Einstein background from the correlation functions. All three methods give consistent results. The measured lengths of homogeneity are studied as functions of particle multiplicity as well as average pair transverse momentum and mass. The results are compared with data from both CMS and ATLAS at $\sqrt{s} =$ 7 TeV, as well as with theoretical predictions

Search for dark matter in events with a leptoquark and missing transverse momentum in proton-proton collisions at 13 TeV

A search is presented for dark matter in proton-proton collisions at a center-of-mass energy of root s= 13 TeV using events with at least one high transverse momentum (p(T)) muon, at least one high-p(T) jet, and large missing transverse momentum. The data were collected with the CMS detector at the CERN LHC in 2016 and 2017, and correspond to an integrated luminosity of 77.4 fb(-1). In the examined scenario, a pair of scalar leptoquarks is assumed to be produced. One leptoquark decays to a muon and a jet while the other decays to dark matter and low-p(T) standard model particles. The signature for signal events would be significant missing transverse momentum from the dark matter in conjunction with a peak at the leptoquark mass in the invariant mass distribution of the highest p(T) muon and jet. The data are observed to be consistent with the background predicted by the standard model. For the first benchmark scenario considered, dark matter masses up to 500 GeV are excluded for leptoquark masses m(LQ) approximate to 1400 GeV, and up to 300 GeV for m(LQ) approximate to 1500 GeV. For the second benchmark scenario, dark matter masses up to 600 GeV are excluded for m(LQ) approximate to 1400 GeV. (C) 2019 The Author(s). Published by Elsevier B.V.Peer reviewe

Search for an L-mu - L-tau gauge boson using Z -> 4 mu events in proton-proton collisions at root s=13 TeV

A search for a narrow Z' gauge boson with a mass between 5 and 70 GeV resulting from an L-mu - L-tau U (1) local gauge symmetry is reported. Theories that predict such a particle have been proposed as an explanation of various experimental discrepancies, including the lack of a dark matter signal in direct-detection experiments, tension in the measurement of the anomalous magnetic moment of the muon, and reports of possible lepton flavor universality violation in B meson decays. A data sample of proton-proton collisions at a center-of-mass energy of 13 TeV is used, corresponding to an integrated luminosity of 77.3 fb(-1) recorded in 2016 and 2017 by the CMS detector at the LHC. Events containing four muons with an invariant mass near the standard model Z boson mass are analyzed, and the selection is further optimized to be sensitive to the events that may contain Z -> Z'mu mu -> 4 mu decays. The event yields are consistent with the standard model predictions. Upper limits of 10(-8)-10(-7) at 95% confidence level are set on the product of branching fractions B(Z -> Z'mu mu)B(Z' -> mu mu), depending on the Z' mass, which excludes a Z' boson coupling strength to muons above 0.004-0.3. These are the first dedicated limits on L-mu - L-tau models at the LHC and result in a significant increase in the excluded model parameter space. The results of this search may also be used to constrain the coupling strength of any light Z' gauge boson to muons. (C) 2019 The Author(s). Published by Elsevier B.V.Peer reviewe